Harvey, Therese

Abstract [en]

Earth observation satellites cover large areas with frequent temporal repetition and provide us with new insight into ocean and coastal processes. Ocean colour measurements from satellite remote sensing are linked to the bio-optics, which refers to the light interactions with living organisms and dissolved and suspended constituents in the aquatic environment. Human pressures have changed the aquatic ecosystems, by, for example, the increased input of nutrient and organic matter leading to eutrophication. This thesis aims to study and develop the link between bio-optical data and the remote sensing method to the monitoring and management of the Baltic Sea. The results are applied to the European Union’s Water Directives, and the Baltic Sea Action Plan from the Helsinki commission. In paper I indicators for eutrophication, chlorophyll-a concentration and Secchi depth were evaluated as a link to remote sensing observations. Chlorophyll-a measurements from an operational satellite service (paper I) were compared to conventional ship-based monitoring in paper II and showed high correlations to the in situ data. The results in paper I, II and IV show that the use of remote sensing can improve both the spatial and temporal monitoring of water quality. The number of observations increased when also using satellite data, thus facilitating the assessment of the ecological and environmental status within the European Union’s water directives. The spatial patterns make it possible to study the changes of e.g. algae blooms and terrestrial input on larger scales. Furthermore, the water quality products from satellites can offer a more holistic and easily accessible view of the information to decision makers and end-users. In paper III variable relationships between in situ bio-optical parameters, such as coloured dissolved organic matter (CDOM), dissolved organic carbon, salinity and Secchi depth, were found in different parts of the Baltic Sea. In paper IV an in situ empirical model to retrieve suspended particulate matter (SPM) from turbidity was developed and applied to remote sensing data. The use of Secchi depth as an indicator for eutrophication linked to the concentrations of chlorophyll-a and SPM and CDOM absorption was investigated in paper V. The variations in Secchi depth were affected differently by the mentioned parameters in the different regions. Therefore, one must also consider those when evaluating changes in Secchi depth and for setting target levels for water bodies. This thesis shows good examples on the benefits of incorporating bio-optical and remote sensing data to a higher extent within monitoring and management of the Baltic Sea.

Philipson, Petra

Abstract [en]

In this study the use of ocean color data as a diagnostic tool in integrated coastal zone management was investigated as part of the Science Policy Integration for Coastal Systems Assessment (SPICOSA) project. Parallel to this, an operational coastal monitoring system has been set up in close collaboration with end-users. The core work of the bio-optical part in the project was to develop Secchi depth and attenuation of light as indicators for coastal zone management, by linking remote sensing with the socio-economic and ecological model developed in SPICOSA. The article emphasizes the benefits of stakeholder involvement and end-user feedback for efficient and improved system development. Furthermore, conceptual models were developed on how to integrate remote sensing data into coastal zone management and into a physical-biological model of the Baltic Sea. One of the work packages in the SPICOSA project was academic training. In this work package, on-line teaching material in the field of remote sensing and bio-optics was developed and disseminated on the SETnet web page. The article presented here may act as supportive material for training in bio-optics and remote sensing.

Philipson, Petra

Abstract [en]

The coastal zones are the most inhabited areas of the world and are therefore strongly affected by humans, leading to undesirable environmental changes that may alter the ecosystems, such as eutrophication. In order to evaluate changes in the environment an effective water quality monitoring system for the coastal zones must be in place. The chlorophyll-a concentration is commonly used as a proxy for phytoplankton biomass and as indicator for eutrophication and it can be retrieved from ocean colour remote sensing data. Several operational monitoring systems based on remote sensing are in place to monitor the open sea and, to some extent, the coastal zones. However, evaluations of coastal monitoring systems based on satellite data are scarce. This paper compares the chlorophyll-a concentrations retrieved from an operational satellite system based on MERIS (Medium Resolution Imaging Spectrophotometer) data with ship-based monitoring for the productive seasons in 2008 and 2010, in a coastal area in the Baltic Sea. The comparisons showed that the satellite-based monitoring system is reliable and that the estimations of chlorophyll-a concentration are comparable to in situ measurements in terms of accuracy and quantitative retrieval. A very strong correlation was found between measurements from satellite-derived chlorophyll-a compared to in situ measurements taken close in time (0-3 days), with RMSE of 64% and a MNB of 17%. The comparison of the monthly means showed improved RMSE and a MNB of only 8%. Furthermore, this study shows that MERIS is better at capturing spatial dynamics and the extent of phytoplankton blooms than ship-based monitoring, since it has a synoptic view and higher temporal resolution. Satellite-based monitoring also increases the frequency of chlorophyll-a observations considerably, where the degree of improvement is dependent on the sampling frequency of the respective monitoring programme. Our results show that ocean colour remote sensing can, when combined with field sampling, provide an improved basis for more effective monitoring and management of the coastal zone. These results are important for eutrophication assessment and status classifications of water basins and can be applied to a larger extent within national and international agreements considering the coastal zones, e.g. the European Commission's Water Framework Directive.

Andersson, Agneta

Abstract [en]

Due to high terrestrial runoff, the Baltic Sea isrich in dissolved organic carbon (DOC), the light-absorbing fraction of which is referred to as coloreddissolved organic matter (CDOM). Inputs of DOC andCDOM are predicted to increase with climate change,affecting coastal ecosystems. We found that therelationships between DOC, CDOM, salinity, and Secchidepth all differed between the two coastal areas studied; theW Gulf of Bothnia with high terrestrial input and the NWBaltic Proper with relatively little terrestrial input. TheCDOM:DOC ratio was higher in the Gulf of Bothnia,where CDOM had a greater influence on the Secchi depth,which is used as an indicator of eutrophication and henceimportant for Baltic Sea management. Based on the resultsof this study, we recommend regular CDOM measurements in monitoring programmes, to increase the value ofconcurrent Secchi depth measurements.

Vaiciute, Diana

Abstract [en]

Suspended particulate matter (SPM) causes most of the scattering in natural waters and thus has a strong influence on the underwater light field, and consequently on the whole ecosystem. Turbidity is related to the concentration of SPM which usually is measured gravimetrically, a rather time-consuming method. Measuring turbidity is quick and easy, and therefore also more cost-effective. When derived from remote sensing data the method becomes even more cost-effective because of the good spatial resolution of satellite data and the synoptic capability of the method. Turbidity is also listed in the European Union's Marine Strategy Framework Directive as a supporting monitoring parameter, especially in the coastal zone. In this study, we aim to provide a new Baltic Sea algorithm to retrieve SPM concentration from in situ turbidity and investigate how this can be applied to satellite data. An in situ dataset was collected in Swedish coastal waters to develop a new SPM model. The model was then tested against independent datasets from both Swedish and Lithuanian coastal waters. Despite the optical variability in the datasets, SPM and turbidity were strongly correlated (r = 0.97). The developed model predicts SPM reliably from in situ turbidity (R-2 = 0.93) with a mean normalized bias (MNB) of 2.4% for the Swedish and 14.0% for the Lithuanian datasets, and a relative error (RMS) of 25.3% and 37.3%, respectively. In the validation dataset, turbidity ranged from 0.3 to 49.8 FNU (Formazin Nephelometric Unit) and correspondingly, SPM concentration ranged from 0.3 to 34.0 g m(-3) which covers the ranges typical for Baltic Sea waters. Next, the medium-resolution imaging spectrometer (MERIS) standard SPM product MERIS Ground Segment (MEGS) was tested on all available match-up data (n = 67). The correlation between SPM retrieved from MERIS and in situ SPM was strong for the Swedish dataset with r = 0.74 (RMS = 47.4 and MNB = 11.3%; n = 32) and very strong for the Lithuanian dataset with r = 0.94 (RMS = 29.5% and MNB = -1.5%; n = 35). Then, the turbidity was derived from the MERIS standard SPM product using the new in situ SPM model, but retrieving turbidity from SPM instead. The derived image was then compared to existing in situ data and showed to be in the right range of values for each sub-area. The new SPM model provides a robust and cost-efficient method to determine SPM from in situ turbidity measurements (or vice versa). The developed SPM model predicts SPM concentration with high quality despite the high coloured dissolved organic matter (CDOM) range in the Baltic Sea. By applying the developed SPM model to already existing remote sensing data (MERIS/Envisat) and most importantly to a new generation of satellite sensors (in particular OLCI on board the Sentinel-3), it is possible to derive turbidity for the Baltic Sea.

Walve, Jakob

Karlson, Bengt

Andersson, Agneta

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(English)Manuscript (preprint) (Other academic)

Abstract [en]

Successful management of coastal environments requires reliable monitoring methods and indicators. Secchi depth and chlorophyll-a concentration (Chl-a) are used as indicators for the assessment of eutrophication, both within the European Commission’s Water Framework and Marine Strategy Directives and the Helsinki commission. Chl-a is a used as a proxy for phytoplankton biomass and Secchi depth is used as a measure of changes in Chl-a. However, Secchi depth is more closely correlated with the light climate, affecting for example benthic vegetation. The public strongly link Secchi depth to the perceived water quality. Due to its simple measurement method Secchi depth is included in many monitoring programmes, often with the longest available time-series. In optically complex waters, Secchi depth is influenced by other factors than Chl-a, such as coloured dissolved organic matter (CDOM) and suspended particulate matter (SPM). In this study we evaluate how much Chl-a, CDOM and inorganic SPM each contribute to the variations in Secchi depth. We collected in situ data from different Swedish coastal gradients in three regions, Bothnian Sea, Baltic proper and Skagerrak during 2010-2014. Two linear multiple regression models for each region, with Chl-a, CDOM and inorganic SPM as predictors, explained the Secchi depth well (R2adj=0.54/0.8 for the Bothnian Sea, R2adj=0.81/0.81 for the Baltic proper and R2adj=0.53/0.64 for the Skagerrak). The slope for inorganic SPM was not significant in all models, but still included in the models, as significant correlations were found, both with Secchi depth and between parameters. The follow-up analysis of the multiple regressions by commonality analyses showed differences between the regions in the unique and common effects of the variables to the variance of the R2adj for Secchi depth. In the Bothnian Sea the unique effects for Chl-a were relatively low, 6% and 20%. The highest unique effect were from CDOM (~46% in summer and 20% in spring), whereas inorganic SPM had no unique contribution in summer but in spring with ~6%. The common effects from CDOM and inorganic SPM were large (71% in spring and 42% in summer). In the Baltic proper the optical variables had a different effect on the Secchi depth, with the largest part from the common effects of all three parameters, explaining up to 42-45% of the variations. The largest unique effects were from inorganic SPM (24%) or from Chl-a (15%). The models in the Skagerrak showed another pattern with CDOM having a very high unique effect, 71% for one model and the almost equally to Chl-a in the other 26% (Chl-a 28%). The common effects between CDOM and Chl-a were also pronounced, ~21% and the inorganic SPM had the lowest effect. The models were used for applying the levels for the reference value and the threshold for good/moderate status for Chl-a within the EU directives. The results showed, that in optically complex waters, Secchi depth is not a sufficient indicator for eutrophication, or as a response to Chl-a changes. Differences in natural processes have an indirect effect on the optical components determining the Secchi depth. For example land and river run-off, resuspension, bottom substrate, hydrography and salinity may explain the differences seen between the regions. The natural coastal gradients in Secchi depth will influence the determination of reference conditions for other eutrophication indicators, such as the depth distribution of macro algae. Hence, setting targets for Secchi depth based on reducing Chl-a might in some cases have no or only limited effect.